Josh Dillon, Last Revised January 2022
This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')
antenna = "141" csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_" auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')
Found 47 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_ Found 45 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0
def jd_to_summary_url(jd):
return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'
def jd_to_auto_metrics_url(jd):
return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'
this_antenna = None
jds = []
# parse information about antennas and nodes
for csv in csvs:
df = pd.read_csv(csv)
for n in range(len(df)):
# Add this day to the antenna
row = df.loc[n]
if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
else:
antnum = int(row['Ant'])
if antnum != int(antenna):
continue
if np.issubdtype(type(row['Node']), np.integer):
row['Node'] = str(row['Node'])
if type(row['Node']) == str and row['Node'].isnumeric():
row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
if this_antenna is None:
this_antenna = Antenna(row['Ant'], row['Node'])
jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
jds.append(jd)
this_antenna.add_day(jd, row)
break
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]
df = pd.DataFrame(to_show)
# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
df[col] = bar_cols[col]
z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
df[col] = z_score_cols[col]
ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
df[col] = ant_metrics_cols[col]
redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]
for col in redcal_cols:
df[col] = redcal_cols[col]
# style dataframe
table = df.style.hide_index()\
.applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
.background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
.background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
.background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
.background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
.applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
.applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
.applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
.applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
.bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
.format({col: '{:,.4f}'.format for col in z_score_cols}) \
.format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
.format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
.set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])
This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))
| JDs | A Priori Status | Auto Metrics Flags | Dead Fraction in Ant Metrics (Jee) | Dead Fraction in Ant Metrics (Jnn) | Crossed Fraction in Ant Metrics | Flag Fraction Before Redcal | Flagged By Redcal chi^2 Fraction | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | Average Dead Ant Metric (Jee) | Average Dead Ant Metric (Jnn) | Average Crossed Ant Metric | Median chi^2 Per Antenna (Jee) | Median chi^2 Per Antenna (Jnn) |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2459862 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -1.494389 | 6.914883 | 4.228776 | 30.122425 | 0.916239 | 13.634681 | -0.295642 | -2.898730 | 0.6931 | 0.6871 | 0.4041 | nan | nan |
| 2459861 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -0.986815 | 3.612219 | -1.699301 | 2.688404 | 0.625094 | 0.896248 | 0.007130 | -4.448018 | 0.7221 | 0.6651 | 0.4045 | nan | nan |
| 2459860 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -1.483322 | 5.036391 | 3.991582 | 22.888750 | 0.603210 | 16.299078 | 0.019851 | -3.375434 | 0.7300 | 0.6730 | 0.3990 | nan | nan |
| 2459859 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -1.039716 | 3.032027 | -2.068807 | 2.728058 | -0.579064 | 0.874516 | -0.570730 | -2.884193 | 0.7347 | 0.6802 | 0.3936 | nan | nan |
| 2459858 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | -1.017400 | 3.376123 | -2.068783 | 2.564131 | 0.190097 | 0.700836 | -0.234917 | -4.611331 | 0.7431 | 0.6831 | 0.4082 | 1.557665 | 1.418682 |
| 2459857 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | - | - | 4.498824 | 31.238412 | -0.731301 | 4.072050 | 9.253659 | 12.810024 | 2.618901 | 1.651354 | 0.0298 | 0.0299 | 0.0062 | nan | nan |
| 2459856 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 2.165282 | 3.773983 | -0.061720 | 6.382134 | 1.760148 | 3.983073 | 2.090105 | 17.496414 | 0.7186 | 0.6771 | 0.3741 | 3.362377 | 3.064032 |
| 2459855 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 2.975584 | 5.857752 | -0.713258 | 7.124383 | 2.499749 | 4.364898 | 2.390350 | 12.315455 | 0.7046 | 0.6932 | 0.3971 | 3.363372 | 2.808851 |
| 2459854 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 2.508297 | 5.300506 | -0.599181 | 5.124733 | 1.770747 | 3.150846 | 2.195717 | 25.660869 | 0.7120 | 0.7126 | 0.4093 | 3.458832 | 2.864514 |
| 2459853 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 1.689347 | 4.333025 | -0.595114 | 7.172965 | 0.902327 | 4.449920 | 2.003782 | 35.899568 | 0.7383 | 0.6671 | 0.4006 | 3.662871 | 3.189004 |
| 2459852 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 3.656627 | 4.754660 | -0.178519 | 7.632438 | 1.207203 | 3.868506 | 0.718092 | 8.883914 | 0.8258 | 0.8193 | 0.2264 | 6.412342 | 6.667709 |
| 2459851 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 1.853024 | 6.560627 | -0.538867 | 10.255183 | 2.985618 | 7.717310 | 4.076287 | 24.665452 | 0.7570 | 0.7053 | 0.3162 | 2.736310 | 1.962893 |
| 2459850 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 1.684994 | 4.312794 | -0.597106 | 6.940594 | 1.299271 | 4.533738 | 2.579298 | 33.539998 | 0.7423 | 0.7372 | 0.3314 | 3.205350 | 2.720492 |
| 2459849 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 1.854971 | 3.600406 | -0.349885 | 13.770495 | 1.315994 | 4.465277 | 2.893396 | 32.023280 | 0.7432 | 0.7273 | 0.3386 | 4.422671 | 3.882419 |
| 2459848 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 2.137598 | 4.071901 | 0.601490 | 8.985149 | 1.080515 | 4.597780 | 0.404120 | 26.959665 | 0.7220 | 0.7307 | 0.3577 | 3.827483 | 3.419790 |
| 2459847 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 2.188537 | 5.966313 | 1.137092 | 9.287319 | 1.264573 | 2.694482 | 3.166647 | 20.782080 | 0.7199 | 0.6557 | 0.4124 | 8.625949 | 6.969488 |
| 2459845 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 2.725836 | 4.042788 | 1.022961 | 11.363612 | 2.328536 | 3.123032 | 2.226000 | 15.172467 | 0.7190 | 0.7127 | 0.3715 | 0.000000 | 0.000000 |
| 2459844 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | - | - | -1.023092 | 10.123497 | -0.084877 | 4.023408 | 0.433450 | 21.774068 | 1.022486 | 58.797060 | 0.0289 | 0.0264 | 0.0019 | nan | nan |
| 2459843 | digital_ok | 100.00% | 1.20% | 0.66% | 0.00% | 100.00% | 0.00% | 3.583530 | 5.342074 | 1.734576 | 5.393391 | 1.905014 | 6.950482 | 3.556892 | 35.274483 | 0.7270 | 0.7165 | 0.3791 | 0.000000 | 0.000000 |
| 2459842 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 0.596080 | 1.214093 | 1.319622 | 3.124296 | 0.619831 | -0.138113 | 0.743953 | 7.933467 | 0.7397 | 0.6577 | 0.2550 | 4.169269 | 4.583039 |
| 2459841 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | - | - | 0.436855 | 10.135161 | 0.880181 | 2.464039 | 0.055431 | 44.924105 | 2.026694 | 57.531923 | 0.0287 | 0.0261 | 0.0020 | nan | nan |
| 2459839 | digital_ok | 100.00% | - | - | - | - | - | 0.451112 | 2.939704 | -0.629236 | 0.873077 | -0.658835 | 0.611282 | 0.862796 | 7.302672 | nan | nan | nan | nan | nan |
| 2459838 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 2.333315 | 5.150028 | 2.394792 | 7.130575 | -0.148684 | 6.280166 | 0.416003 | 14.843015 | 0.7520 | 0.7023 | 0.3732 | 5.653682 | 5.227910 |
| 2459836 | digital_ok | - | 100.00% | 100.00% | 0.00% | - | - | nan | nan | nan | nan | nan | nan | nan | nan | 0.0572 | 0.0549 | 0.0042 | nan | nan |
| 2459835 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | - | - | -0.821672 | 2.205879 | 0.632639 | 2.771556 | -0.419382 | 1.553314 | 0.218252 | 4.875010 | 0.0539 | 0.0553 | 0.0030 | nan | nan |
| 2459833 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | - | - | 1.491410 | 2.497130 | 1.681315 | 2.308096 | -0.071514 | 3.722491 | 1.519298 | 12.723796 | 0.0442 | 0.0382 | 0.0021 | nan | nan |
| 2459832 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 2.649230 | 5.773857 | 2.155520 | 6.165710 | -0.113652 | 0.214608 | 0.955313 | 17.447285 | 0.8161 | 0.5428 | 0.5704 | 5.606297 | 4.141589 |
| 2459831 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | - | - | 0.195996 | 2.823740 | -0.675595 | 1.111004 | -0.835554 | 1.025139 | 0.497327 | 5.361093 | 0.0582 | 0.0556 | 0.0074 | nan | nan |
| 2459830 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 2.921866 | 4.412641 | 3.049025 | 7.862212 | 1.240602 | 3.399525 | 1.755748 | 30.946777 | 0.8170 | 0.5605 | 0.5502 | 6.382113 | 5.671474 |
| 2459829 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 3.710150 | 5.623689 | 2.657248 | 6.762318 | 11.336877 | 1.324904 | 5.886479 | 47.253044 | 0.7586 | 0.6699 | 0.3916 | 0.000000 | 0.000000 |
| 2459828 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 2.883248 | 3.340048 | -0.103845 | 7.291701 | 1.387250 | 3.327442 | 1.721418 | 61.258787 | 0.8185 | 0.5710 | 0.5362 | 6.727250 | 5.087120 |
| 2459827 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 2.541244 | 4.151928 | 0.453567 | 9.712322 | 1.014735 | 2.017006 | 7.435981 | 15.233342 | 0.7695 | 0.6667 | 0.3948 | 6.907913 | 4.303553 |
| 2459826 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 2.556702 | 2.969637 | 0.482685 | 9.522345 | 1.952994 | 3.052109 | 1.468391 | 32.789249 | 0.8160 | 0.5797 | 0.5157 | 0.000000 | 0.000000 |
| 2459825 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 2.569833 | 3.863638 | -0.689497 | 7.690181 | 0.775866 | 1.795674 | 3.331989 | 6.146356 | 0.8193 | 0.6056 | 0.5071 | -0.000000 | -0.000000 |
| 2459824 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 2.485012 | 7.576156 | -0.836574 | 8.103380 | 0.684652 | 4.460638 | 1.219551 | 30.124668 | 0.7372 | 0.7209 | 0.3286 | 0.000000 | 0.000000 |
| 2459823 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 2.950741 | 5.757542 | -0.013587 | 10.936203 | 0.303055 | 2.427144 | 0.889568 | 18.654453 | 0.7815 | 0.6347 | 0.4534 | 8.082341 | 3.948999 |
| 2459822 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 3.127647 | 3.606226 | 0.385708 | 9.691430 | 0.875133 | 3.567888 | 3.572939 | 34.649618 | 0.8184 | 0.6239 | 0.5070 | 8.961033 | 6.811908 |
| 2459821 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 3.172455 | 4.091988 | 0.222933 | 9.433504 | -0.063330 | 2.307842 | 3.936140 | 7.230794 | 0.8148 | 0.6362 | 0.5002 | 3.586821 | 2.819291 |
| 2459820 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 2.906010 | 3.958772 | 0.323496 | 9.039004 | 0.616822 | 6.636672 | 1.039300 | 35.938943 | 0.7797 | 0.6719 | 0.3981 | 7.203641 | 7.051049 |
| 2459817 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 3.179981 | 4.788648 | -0.021495 | 8.967838 | 0.217072 | 2.303794 | -0.485875 | 3.407464 | 0.8156 | 0.6686 | 0.5000 | 4.575848 | 3.724449 |
| 2459816 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 2.044658 | 3.741543 | -0.896930 | 10.708423 | 0.932257 | 3.298483 | 1.640677 | 35.054148 | 0.8580 | 0.5943 | 0.5783 | 5.854701 | 4.183522 |
| 2459815 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 2.943898 | 5.489737 | -0.577549 | 9.436945 | 0.479744 | 4.501106 | 1.400733 | 27.127667 | 0.8166 | 0.6885 | 0.5006 | 7.050746 | 5.855479 |
| 2459814 | digital_ok | 0.00% | - | - | - | - | - | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| 2459813 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | nan | nan | inf | inf | nan | nan | nan | nan | nan | nan | nan | 0.000000 | 0.000000 |
auto_metrics notebooks.¶htmls_to_display = []
for am_html in auto_metric_htmls:
html_to_display = ''
# read html into a list of lines
with open(am_html) as f:
lines = f.readlines()
# find section with this antenna's metric plots and add to html_to_display
jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
try:
section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
except ValueError:
continue
html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
for line in lines[section_start_line + 1:]:
html_to_display += line
if '<hr' in line:
htmls_to_display.append(html_to_display)
break
These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.
for i, html_to_display in enumerate(htmls_to_display):
if i == 100:
break
display(HTML(html_to_display))
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 141 | N13 | digital_ok | nn Power | 30.122425 | -1.494389 | 6.914883 | 4.228776 | 30.122425 | 0.916239 | 13.634681 | -0.295642 | -2.898730 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 141 | N13 | digital_ok | nn Shape | 3.612219 | 3.612219 | -0.986815 | 2.688404 | -1.699301 | 0.896248 | 0.625094 | -4.448018 | 0.007130 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 141 | N13 | digital_ok | nn Power | 22.888750 | -1.483322 | 5.036391 | 3.991582 | 22.888750 | 0.603210 | 16.299078 | 0.019851 | -3.375434 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 141 | N13 | digital_ok | nn Shape | 3.032027 | -1.039716 | 3.032027 | -2.068807 | 2.728058 | -0.579064 | 0.874516 | -0.570730 | -2.884193 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 141 | N13 | digital_ok | nn Shape | 3.376123 | 3.376123 | -1.017400 | 2.564131 | -2.068783 | 0.700836 | 0.190097 | -4.611331 | -0.234917 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 141 | N13 | digital_ok | nn Shape | 31.238412 | 31.238412 | 4.498824 | 4.072050 | -0.731301 | 12.810024 | 9.253659 | 1.651354 | 2.618901 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 141 | N13 | digital_ok | nn Temporal Discontinuties | 17.496414 | 2.165282 | 3.773983 | -0.061720 | 6.382134 | 1.760148 | 3.983073 | 2.090105 | 17.496414 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 141 | N13 | digital_ok | nn Temporal Discontinuties | 12.315455 | 5.857752 | 2.975584 | 7.124383 | -0.713258 | 4.364898 | 2.499749 | 12.315455 | 2.390350 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 141 | N13 | digital_ok | nn Temporal Discontinuties | 25.660869 | 5.300506 | 2.508297 | 5.124733 | -0.599181 | 3.150846 | 1.770747 | 25.660869 | 2.195717 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 141 | N13 | digital_ok | nn Temporal Discontinuties | 35.899568 | 4.333025 | 1.689347 | 7.172965 | -0.595114 | 4.449920 | 0.902327 | 35.899568 | 2.003782 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 141 | N13 | digital_ok | nn Temporal Discontinuties | 8.883914 | 3.656627 | 4.754660 | -0.178519 | 7.632438 | 1.207203 | 3.868506 | 0.718092 | 8.883914 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 141 | N13 | digital_ok | nn Temporal Discontinuties | 24.665452 | 1.853024 | 6.560627 | -0.538867 | 10.255183 | 2.985618 | 7.717310 | 4.076287 | 24.665452 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 141 | N13 | digital_ok | nn Temporal Discontinuties | 33.539998 | 1.684994 | 4.312794 | -0.597106 | 6.940594 | 1.299271 | 4.533738 | 2.579298 | 33.539998 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 141 | N13 | digital_ok | nn Temporal Discontinuties | 32.023280 | 1.854971 | 3.600406 | -0.349885 | 13.770495 | 1.315994 | 4.465277 | 2.893396 | 32.023280 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 141 | N13 | digital_ok | nn Temporal Discontinuties | 26.959665 | 4.071901 | 2.137598 | 8.985149 | 0.601490 | 4.597780 | 1.080515 | 26.959665 | 0.404120 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 141 | N13 | digital_ok | nn Temporal Discontinuties | 20.782080 | 5.966313 | 2.188537 | 9.287319 | 1.137092 | 2.694482 | 1.264573 | 20.782080 | 3.166647 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 141 | N13 | digital_ok | nn Temporal Discontinuties | 15.172467 | 4.042788 | 2.725836 | 11.363612 | 1.022961 | 3.123032 | 2.328536 | 15.172467 | 2.226000 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 141 | N13 | digital_ok | nn Temporal Discontinuties | 58.797060 | -1.023092 | 10.123497 | -0.084877 | 4.023408 | 0.433450 | 21.774068 | 1.022486 | 58.797060 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 141 | N13 | digital_ok | nn Temporal Discontinuties | 35.274483 | 5.342074 | 3.583530 | 5.393391 | 1.734576 | 6.950482 | 1.905014 | 35.274483 | 3.556892 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 141 | N13 | digital_ok | nn Temporal Discontinuties | 7.933467 | 0.596080 | 1.214093 | 1.319622 | 3.124296 | 0.619831 | -0.138113 | 0.743953 | 7.933467 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 141 | N13 | digital_ok | nn Temporal Discontinuties | 57.531923 | 0.436855 | 10.135161 | 0.880181 | 2.464039 | 0.055431 | 44.924105 | 2.026694 | 57.531923 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 141 | N13 | digital_ok | nn Temporal Discontinuties | 7.302672 | 2.939704 | 0.451112 | 0.873077 | -0.629236 | 0.611282 | -0.658835 | 7.302672 | 0.862796 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 141 | N13 | digital_ok | nn Temporal Discontinuties | 14.843015 | 5.150028 | 2.333315 | 7.130575 | 2.394792 | 6.280166 | -0.148684 | 14.843015 | 0.416003 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 141 | N13 | digital_ok | nn Temporal Discontinuties | 4.875010 | 2.205879 | -0.821672 | 2.771556 | 0.632639 | 1.553314 | -0.419382 | 4.875010 | 0.218252 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 141 | N13 | digital_ok | nn Temporal Discontinuties | 12.723796 | 2.497130 | 1.491410 | 2.308096 | 1.681315 | 3.722491 | -0.071514 | 12.723796 | 1.519298 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 141 | N13 | digital_ok | nn Temporal Discontinuties | 17.447285 | 2.649230 | 5.773857 | 2.155520 | 6.165710 | -0.113652 | 0.214608 | 0.955313 | 17.447285 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 141 | N13 | digital_ok | nn Temporal Discontinuties | 5.361093 | 0.195996 | 2.823740 | -0.675595 | 1.111004 | -0.835554 | 1.025139 | 0.497327 | 5.361093 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 141 | N13 | digital_ok | nn Temporal Discontinuties | 30.946777 | 2.921866 | 4.412641 | 3.049025 | 7.862212 | 1.240602 | 3.399525 | 1.755748 | 30.946777 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 141 | N13 | digital_ok | nn Temporal Discontinuties | 47.253044 | 5.623689 | 3.710150 | 6.762318 | 2.657248 | 1.324904 | 11.336877 | 47.253044 | 5.886479 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 141 | N13 | digital_ok | nn Temporal Discontinuties | 61.258787 | 3.340048 | 2.883248 | 7.291701 | -0.103845 | 3.327442 | 1.387250 | 61.258787 | 1.721418 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 141 | N13 | digital_ok | nn Temporal Discontinuties | 15.233342 | 2.541244 | 4.151928 | 0.453567 | 9.712322 | 1.014735 | 2.017006 | 7.435981 | 15.233342 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 141 | N13 | digital_ok | nn Temporal Discontinuties | 32.789249 | 2.969637 | 2.556702 | 9.522345 | 0.482685 | 3.052109 | 1.952994 | 32.789249 | 1.468391 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 141 | N13 | digital_ok | nn Power | 7.690181 | 3.863638 | 2.569833 | 7.690181 | -0.689497 | 1.795674 | 0.775866 | 6.146356 | 3.331989 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 141 | N13 | digital_ok | nn Temporal Discontinuties | 30.124668 | 2.485012 | 7.576156 | -0.836574 | 8.103380 | 0.684652 | 4.460638 | 1.219551 | 30.124668 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 141 | N13 | digital_ok | nn Temporal Discontinuties | 18.654453 | 5.757542 | 2.950741 | 10.936203 | -0.013587 | 2.427144 | 0.303055 | 18.654453 | 0.889568 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 141 | N13 | digital_ok | nn Temporal Discontinuties | 34.649618 | 3.127647 | 3.606226 | 0.385708 | 9.691430 | 0.875133 | 3.567888 | 3.572939 | 34.649618 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 141 | N13 | digital_ok | nn Power | 9.433504 | 4.091988 | 3.172455 | 9.433504 | 0.222933 | 2.307842 | -0.063330 | 7.230794 | 3.936140 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 141 | N13 | digital_ok | nn Temporal Discontinuties | 35.938943 | 2.906010 | 3.958772 | 0.323496 | 9.039004 | 0.616822 | 6.636672 | 1.039300 | 35.938943 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 141 | N13 | digital_ok | nn Power | 8.967838 | 3.179981 | 4.788648 | -0.021495 | 8.967838 | 0.217072 | 2.303794 | -0.485875 | 3.407464 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 141 | N13 | digital_ok | nn Temporal Discontinuties | 35.054148 | 3.741543 | 2.044658 | 10.708423 | -0.896930 | 3.298483 | 0.932257 | 35.054148 | 1.640677 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 141 | N13 | digital_ok | nn Temporal Discontinuties | 27.127667 | 5.489737 | 2.943898 | 9.436945 | -0.577549 | 4.501106 | 0.479744 | 27.127667 | 1.400733 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 141 | N13 | digital_ok | nn Shape | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 141 | N13 | digital_ok | nn Shape | nan | nan | nan | inf | inf | nan | nan | nan | nan |